Model Collapse

Model Collapse?

I read this article from Futurism and it made me stop and ruminate.

The core principle of this article is that when we train AI on AI-generated content, we’re creating a feedback loop of sameness — what researchers call model collapse or digital inbreeding.

So why is this a problem ? The internet was already biased after all.

Consider this analogy - 🧠 Human data = a wild, messy rainforest 🤖 AI data = a smooth, sterile monocrop

So what happens after AI gets trained on AI generated material ?

🔁 Each generation becomes a blurrier copy of the last. 📉 Nuance disappears. 📈 Biases harden. 💡 Creativity dies.

We risk replacing a diverse, chaotic, but rich world with a hollow echo chamber. So -

1. Are we building smarter AI — or just smarter mirrors?
2. How do we measure data diversity? Can we develop metrics to track when datasets become too homogenized?
3. If future AIs are trained on “echoes,” will they still be able to teach us something new?

#AI #ModelCollapse #DataDiversity #FutureOfAI #TechEthics #AIKiran #ThoughtLeadership #WomenWhoCode #WomenInTech